fix: resolve Model Issues and add huggingface dependency (#2339)
* chore: adding default values to Azure OpenAI mandatory component * fix: huggingface model component: - Change Huggingface-hub version from 0.20.0 to 0.22.0; - Internal model_id resolver not working, create a field to model_id; * feat: add HuggingFace as extra dependency * chore: remove redundant atribution on children * fix: remove user environment variables from ChatLiteLLMModelComponent --------- Co-authored-by: joaoguilhermeS <j.guilherme.s.oliveira2@gmail.com>
This commit is contained in:
João Pedro Miranda C. Hluchan
GitHub
parent
2787bec4fb
commit
805df8298a
5 changed files with 65 additions and 66 deletions
42
poetry.lock
generated
42
poetry.lock
generated
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@ -3434,36 +3434,38 @@ files = [
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[[package]]
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name = "huggingface-hub"
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version = "0.20.3"
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version = "0.22.2"
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description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
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optional = false
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python-versions = ">=3.8.0"
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files = [
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{file = "huggingface_hub-0.20.3-py3-none-any.whl", hash = "sha256:d988ae4f00d3e307b0c80c6a05ca6dbb7edba8bba3079f74cda7d9c2e562a7b6"},
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{file = "huggingface_hub-0.20.3.tar.gz", hash = "sha256:94e7f8e074475fbc67d6a71957b678e1b4a74ff1b64a644fd6cbb83da962d05d"},
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{file = "huggingface_hub-0.22.2-py3-none-any.whl", hash = "sha256:3429e25f38ccb834d310804a3b711e7e4953db5a9e420cc147a5e194ca90fd17"},
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{file = "huggingface_hub-0.22.2.tar.gz", hash = "sha256:32e9a9a6843c92f253ff9ca16b9985def4d80a93fb357af5353f770ef74a81be"},
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]
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[package.dependencies]
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aiohttp = {version = "*", optional = true, markers = "extra == \"inference\""}
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filelock = "*"
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fsspec = ">=2023.5.0"
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minijinja = {version = ">=1.0", optional = true, markers = "extra == \"inference\""}
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packaging = ">=20.9"
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pydantic = {version = ">1.1,<3.0", optional = true, markers = "python_version > \"3.8\" and extra == \"inference\""}
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pyyaml = ">=5.1"
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requests = "*"
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tqdm = ">=4.42.1"
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typing-extensions = ">=3.7.4.3"
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[package.extras]
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all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "mypy (==1.5.1)", "numpy", "pydantic (>1.1,<2.0)", "pydantic (>1.1,<3.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.1.3)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
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all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "minijinja (>=1.0)", "mypy (==1.5.1)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.3.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
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cli = ["InquirerPy (==0.3.4)"]
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dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "mypy (==1.5.1)", "numpy", "pydantic (>1.1,<2.0)", "pydantic (>1.1,<3.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.1.3)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
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dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "minijinja (>=1.0)", "mypy (==1.5.1)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.3.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
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fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
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inference = ["aiohttp", "pydantic (>1.1,<2.0)", "pydantic (>1.1,<3.0)"]
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quality = ["mypy (==1.5.1)", "ruff (>=0.1.3)"]
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hf-transfer = ["hf-transfer (>=0.1.4)"]
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inference = ["aiohttp", "minijinja (>=1.0)"]
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quality = ["mypy (==1.5.1)", "ruff (>=0.3.0)"]
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tensorflow = ["graphviz", "pydot", "tensorflow"]
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testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "numpy", "pydantic (>1.1,<2.0)", "pydantic (>1.1,<3.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
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torch = ["torch"]
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tensorflow-testing = ["keras (<3.0)", "tensorflow"]
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testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "minijinja (>=1.0)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
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torch = ["safetensors", "torch"]
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typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)"]
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[[package]]
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@ -5009,6 +5011,23 @@ files = [
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[package.dependencies]
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requests = "*"
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[[package]]
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name = "minijinja"
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version = "2.0.1"
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description = "An experimental Python binding of the Rust MiniJinja template engine."
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optional = false
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python-versions = ">=3.8"
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files = [
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{file = "minijinja-2.0.1-cp38-abi3-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:063b291cb31f5c33eb77bb4cb457f67f14426ca1418232b8ae9f267155d330cc"},
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{file = "minijinja-2.0.1-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4a4e9d639dd89ce7fef86e82147082ab3c248a36950fa3fbe793685ba322c1b7"},
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{file = "minijinja-2.0.1-cp38-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:a20373af4ee5430356c196c7fe5f19e3261a4fa16c944542b4de7a2349bac7a6"},
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{file = "minijinja-2.0.1-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ade637bf4826258811a785ccc4e5d41cd2bdf4ec317b1ed3daa4dbbdd020f37d"},
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{file = "minijinja-2.0.1-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:d5ec956d777e0fee8e214af48363334c04f098e986038a9e8cb92a0564f81943"},
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{file = "minijinja-2.0.1-cp38-abi3-win32.whl", hash = "sha256:039f4d1a1a73f90917cff1ed7c617eb56e2b2f91bbbdc551adaa448e1673e5c2"},
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{file = "minijinja-2.0.1-cp38-abi3-win_amd64.whl", hash = "sha256:dca5d7689905dce340e36e47348b505c788daf297253b85a1aff506ea63ad1b8"},
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{file = "minijinja-2.0.1.tar.gz", hash = "sha256:e774beffebfb8a1ad17e638ef70917cf5e94593f79acb8a8fff7d983169f3a4e"},
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]
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[[package]]
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name = "mkl"
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version = "2021.4.0"
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@ -5671,6 +5690,7 @@ description = "Nvidia JIT LTO Library"
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optional = true
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python-versions = ">=3"
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files = [
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{file = "nvidia_nvjitlink_cu12-12.5.40-py3-none-manylinux2014_aarch64.whl", hash = "sha256:004186d5ea6a57758fd6d57052a123c73a4815adf365eb8dd6a85c9eaa7535ff"},
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{file = "nvidia_nvjitlink_cu12-12.5.40-py3-none-manylinux2014_x86_64.whl", hash = "sha256:d9714f27c1d0f0895cd8915c07a87a1d0029a0aa36acaf9156952ec2a8a12189"},
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{file = "nvidia_nvjitlink_cu12-12.5.40-py3-none-win_amd64.whl", hash = "sha256:c3401dc8543b52d3a8158007a0c1ab4e9c768fcbd24153a48c86972102197ddd"},
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]
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@ -10555,4 +10575,4 @@ local = ["ctransformers", "llama-cpp-python", "sentence-transformers"]
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[metadata]
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lock-version = "2.0"
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python-versions = ">=3.10,<3.13"
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content-hash = "3e72b6faa1c674615a7e5dec3e7d962349e736bf6675c08a49080b7f336cc75b"
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content-hash = "14772c35473f812d12f117d18c1a861da9dda27492e8e0007fbd76f4eeac9ab4"
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@ -30,7 +30,7 @@ langflow-base = { path = "./src/backend/base", develop = true }
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beautifulsoup4 = "^4.12.2"
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google-search-results = "^2.4.1"
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google-api-python-client = "^2.130.0"
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huggingface-hub = { version = "^0.20.0", extras = ["inference"] }
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huggingface-hub = { version = "^0.22.0", extras = ["inference"] }
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llama-cpp-python = { version = "~0.2.0", optional = true }
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networkx = "^3.1"
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fake-useragent = "^1.5.0"
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@ -1,5 +1,3 @@
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from typing import Optional
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from langchain_community.chat_models.litellm import ChatLiteLLM, ChatLiteLLMException
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from langflow.base.constants import STREAM_INFO_TEXT
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@ -12,7 +10,6 @@ from langflow.io import (
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FloatInput,
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IntInput,
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MessageInput,
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Output,
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SecretStrInput,
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StrInput,
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)
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@ -35,7 +32,7 @@ class ChatLiteLLMModelComponent(LCModelComponent):
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),
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SecretStrInput(
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name="api_key",
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display_name="API key",
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display_name="API Key",
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advanced=False,
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required=False,
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),
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@ -59,25 +56,24 @@ class ChatLiteLLMModelComponent(LCModelComponent):
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required=False,
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value=0.7,
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),
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DictInput(
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name="kwargs",
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display_name="Kwargs",
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advanced=True,
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required=False,
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is_list=True,
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value={},
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),
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DictInput(
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name="model_kwargs",
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display_name="Model kwargs",
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advanced=True,
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required=False,
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is_list=True,
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value={},
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),
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FloatInput(
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name="top_p",
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display_name="Top p",
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advanced=True,
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required=False,
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),
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IntInput(
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name="top_k",
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display_name="Top k",
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advanced=True,
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required=False,
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),
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FloatInput(name="top_p", display_name="Top p", advanced=True, required=False, value=0.5),
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IntInput(name="top_k", display_name="Top k", advanced=True, required=False, value=35),
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IntInput(
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name="n",
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display_name="N",
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@ -122,11 +118,6 @@ class ChatLiteLLMModelComponent(LCModelComponent):
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),
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]
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outputs = [
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Output(display_name="Text", name="text_output", method="text_response"),
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Output(display_name="Language Model", name="model_output", method="build_model"),
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]
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def build_model(self) -> LanguageModel: # type: ignore[type-var]
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try:
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import litellm # type: ignore
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@ -137,28 +128,19 @@ class ChatLiteLLMModelComponent(LCModelComponent):
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raise ChatLiteLLMException(
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"Could not import litellm python package. " "Please install it with `pip install litellm`"
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)
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provider_map = {
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"OpenAI": "openai_api_key",
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"Azure": "azure_api_key",
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"Anthropic": "anthropic_api_key",
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"Replicate": "replicate_api_key",
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"Cohere": "cohere_api_key",
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"OpenRouter": "openrouter_api_key",
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}
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# Set the API key based on the provider
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api_keys: dict[str, Optional[str]] = {v: None for v in provider_map.values()}
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if variable_name := provider_map.get(self.provider):
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api_keys[variable_name] = self.api_key
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else:
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raise ChatLiteLLMException(
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f"Provider {self.provider} is not supported. Supported providers are: {', '.join(provider_map.keys())}"
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)
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# Remove empty keys
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if "" in self.kwargs:
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del self.kwargs[""]
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if "" in self.model_kwargs:
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del self.model_kwargs[""]
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# Report missing fields for Azure provider
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if self.provider == "Azure":
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if "api_base" not in self.kwargs:
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raise Exception("Missing api_base on kwargs")
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if "api_version" not in self.model_kwargs:
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raise Exception("Missing api_version on model_kwargs")
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output = ChatLiteLLM(
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model=self.model,
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model=f"{self.provider.lower()}/{self.model}",
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client=None,
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streaming=self.stream,
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temperature=self.temperature,
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@ -168,12 +150,8 @@ class ChatLiteLLMModelComponent(LCModelComponent):
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n=self.n,
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max_tokens=self.max_tokens,
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max_retries=self.max_retries,
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openai_api_key=api_keys["openai_api_key"],
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azure_api_key=api_keys["azure_api_key"],
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anthropic_api_key=api_keys["anthropic_api_key"],
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replicate_api_key=api_keys["replicate_api_key"],
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cohere_api_key=api_keys["cohere_api_key"],
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openrouter_api_key=api_keys["openrouter_api_key"],
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**self.kwargs,
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)
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output.client.api_key = self.api_key
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return output # type: ignore
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@ -4,7 +4,7 @@ from langflow.base.constants import STREAM_INFO_TEXT
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from langflow.base.models.model import LCModelComponent
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from langflow.field_typing import LanguageModel
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from langflow.inputs import MessageTextInput
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from langflow.io import BoolInput, DictInput, DropdownInput, MessageInput, Output
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from langflow.io import BoolInput, DictInput, DropdownInput, MessageInput
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class AmazonBedrockComponent(LCModelComponent):
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@ -64,10 +64,6 @@ class AmazonBedrockComponent(LCModelComponent):
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),
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BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True),
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]
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outputs = [
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Output(display_name="Text", name="text_output", method="text_response"),
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Output(display_name="Language Model", name="model_output", method="build_model"),
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]
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def build_model(self) -> LanguageModel: # type: ignore[type-var]
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model_id = self.model_id
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@ -15,6 +15,11 @@ class HuggingFaceEndpointsComponent(LCModelComponent):
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inputs = [
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MessageInput(name="input_value", display_name="Input"),
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SecretStrInput(name="endpoint_url", display_name="Endpoint URL", password=True),
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StrInput(
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name="model_id",
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display_name="Model Id",
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info="Id field of endpoint_url response.",
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),
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DropdownInput(
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name="task",
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display_name="Task",
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@ -47,5 +52,5 @@ class HuggingFaceEndpointsComponent(LCModelComponent):
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except Exception as e:
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raise ValueError("Could not connect to HuggingFace Endpoints API.") from e
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output = ChatHuggingFace(llm=llm)
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output = ChatHuggingFace(llm=llm, model_id=self.model_id)
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return output # type: ignore
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